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슬러리 생물반응기를 이용한 PAHs 오염토양처리에서 재순환수와 계면활성제의 효과
남궁완(Wan Namkoong),나경진(Kyung-Jin Na) 유기성자원학회 2001 유기물자원화 Vol.9 No.1
PAHs로 오염된 토양을 슬러리 생물반응기로 처리할 경우 재순환수와 계면활성제 첨가가 PAHs 제거율에 미치는 영향을 살펴보고자 하였다. 대부분 실험결과에 서 1차 반응모댈이 0차 반응모델보다 phenanthren과 pyrene의 제거율을 설명하는데 높은 상관계수를 나타냈다. 재순환수 및 CMC(critical micelle concentration)이상으로 계면활성 제 를 첨가한 실험에서 첨가하지 않은 경우 보다 phenanthrene과 pyrene의 제거 율이 향상되었다. This research was carried our to evaluate the effect of recyded wasterwater and surfactant above CMC(criitical mocelle concentration) onthe temoval rate of PAHS in bench-scale slurry bioreator. Kintic patameters based on zero order and fìrst order kinetic models were etimated. The first order model was able to describe the rernoval of phenanthrene and pyrene with high correlaùon coeffcients. Addition of recyded,wastewater could enhance the rernoval rates of phenanthrene and pyrene. Addition of surfàctant above CMC could enhance desorption rate and removal rate of phenanthrene and pyrene.
어안 이미지의 배경 제거 기법을 이용한 실시간 전방향 장애물 감지
최윤원,권기구,김종효,나경진,이석규,Choi, Yun-Won,Kwon, Kee-Koo,Kim, Jong-Hyo,Na, Kyung-Jin,Lee, Suk-Gyu 제어로봇시스템학회 2015 제어·로봇·시스템학회 논문지 Vol.21 No.8
This paper proposes an object detection method based on motion estimation using background subtraction in the fisheye images obtained through omni-directional camera mounted on the vehicle. Recently, most of the vehicles installed with rear camera as a standard option, as well as various camera systems for safety. However, differently from the conventional object detection using the image obtained from the camera, the embedded system installed in the vehicle is difficult to apply a complicated algorithm because of its inherent low processing performance. In general, the embedded system needs system-dependent algorithm because it has lower processing performance than the computer. In this paper, the location of object is estimated from the information of object's motion obtained by applying a background subtraction method which compares the previous frames with the current ones. The real-time detection performance of the proposed method for object detection is verified experimentally on embedded board by comparing the proposed algorithm with the object detection based on LKOF (Lucas-Kanade optical flow).
어안 이미지의 배경 제거 기법을 이용한 실시간 전방향 장애물 감지
최윤원(Yun-Won Choi),권기구(Kee-Koo Kwon),김종효(Jong-Hyo Kim),나경진(Kyung-Jin Na),이석규(Suk-Gyu Lee) 제어로봇시스템학회 2015 제어·로봇·시스템학회 논문지 Vol.18 No.1
This paper proposes an object detection method based on motion estimation using background subtraction in the fisheye images obtained through omni-directional camera mounted on the vehicle. Recently, most of the vehicles installed with rear camera as a standard option, as well as various camera systems for safety. However, differently from the conventional object detection using the image obtained from the camera, the embedded system installed in the vehicle is difficult to apply a complicated algorithm because of its inherent low processing performance. In general, the embedded system needs system-dependent algorithm because it has lower processing performance than the computer. In this paper, the location of object is estimated from the information of object’s motion obtained by applying a background subtraction method which compares the previous frames with the current ones. The real-time detection performance of the proposed method for object detection is verified experimentally on embedded board by comparing the proposed algorithm with the object detection based on LKOF (Lucas-Kanade optical flow).
이인수(In-Soo Lee),이종현(Jong-Hyun Lee),조태현(Tae-Hyun Cho),정명환(Myung-hwan Jeong),태원섭(Won-Sub Tae),김연수(Yeon-Soo Kim),김윤수(Yoon-Soo Kim),나경진(Kyung-Jin Na),하수영(Soo-Young Ha) 대한전자공학회 2018 대한전자공학회 학술대회 Vol.2018 No.6
본 논문에서는 다층 신경회로망과 검사장치 데이터를 이용한 로봇 용접건의 노후화 모니터링 시스템을 제안하였다. 제안한 방법에서는 검사장치로부터 획득한 데이터를 사용하였으며, 이들을 각 다층신경회로망 모듈의 입력 값으로 하여 로봇 용접건의 진단을 수행하였다. 실제 데이터를 이용한 시물레이션을 통해서 제안한 고장진단 시스템의 성능을 확인하였다. In this paper, we propose a fault diagnosis system for state monitoring of the robotic welding gun using MNN(multilayer neural network) and inspection equipment data set. In this method the inspection equipment data were manipulated and used them for diagnosis of robotic welding gun via MNN modules . We carried out the computer simulation with real data to confirm the suitability of the proposed fault diagnosis system.